Purchase planning for direct material requirements largely depends on the master planning systems. Master planning systems generate material requirements by considering demand/forecast for finished goods and exploding the bill of materials to generate projected requirements of raw material and sub-assembly quantities. The master planning systems may consider other factors some examples of which are inventory policies, supply lead times, supply lot-sizes, supplier capacities, on-hand inventory, supplier allocation policies, shipping and receiving calendars for generating the scheduled material requirements. These material requirements are then used for procurement.
However there are two groups of parameters that must be addressed by purchase planning systems. First, it must be able to model and address corporate policy guidelines, some examples of which are inventory levels, fulfillment rates, and approved vendor lists. Second, it must be able to model the contractual terms of the supply agreements with various vendors, some examples of which are obligations, rebates, volume based price breaks, and flex quantity limitations.
The currently existing systems that address master planning and supply chain planning do not adequately address the second groups of requirements above. On the other hand, the currently existing contract management systems do not go beyond modeling the supply contracts, and don't provide any planning capabilities to generate purchase schedules that are compliant with the contracts, as well as the corporate policies.
Therefore the existing systems do not adequately address all the operational constraints that are relevant for purchasing. Partial list of examples of such constraints that remain un-addressed by the existing systems are trading partner terms, conditions and agreements for supply contracts, enterprise business rules and various cost factors that form the landed cost for an item. Another problem that is inadequately addressed by the existing systems is that while the master planning is normally done on a continual basis, tactical and operational purchase planning is not necessarily kept in sync with the latest master planning data. Another example showing this would be the fact that the material requirement patterns change with each master-planning run, but these are not used to determine the best vendor quotas or business splits after each run of master-planning.
Purchase decisions are complex and involve multiple parameters. If these parameters are not considered, possible cost saving opportunities are lost. In addition there could be penalties that could have been avoided or reduced using intelligent planning. For example consider a simple case of two vendors. If there is a contractual obligation to buy a certain quantity of material by a certain week from the first supplier then it may not be an effective decision to buy anything from the second supplier in that week. However, a hard coded allocation solution will automatically decide to buy from the first as well as second vendor based on vendor quota rules and may incur a penalty for not meeting the obligations from the first supplier.
Therefore, an ideal purchase-planning tool should include capabilities to model all the parameters mentioned and other similar parameters all of which are not covered above. It should leverage optimization technologies to minimize the overall cost of direct material purchasing while ensuring complete compliance to the trading partner terms and conditions as well as the corporate business rules. The tool should also provide a system for evaluating the effect of such terms and/or business rules on the overall purchasing costs. The tool should provide simulation capabilities to actually influence the development of supply channel network so as to best meet the purchasing requirements of an enterprise.